We describe an agent architecture that integrates emotions, drives, and behaviors, and that focuses on modeling some of the aspects of emotions as fundamental components within th...
We present a Bayesian clustering algorithm for multivariate time series. A clustering is regarded as a probabilistic model in which the unknown auto-correlation structure of a tim...
SSFisasystemtodiscoverthestructureofsimultaneous equations governing an objective process through experiments. SSF combined with another system SDS to discover a quantitative form...
In this paper, we analyse a concept of total knowledge based on the idea that an agent's total knowledge is the strongest proposition the agent knows. We propose semantics fo...
Reinforcement learning is an effective technique for learning action policies in discrete stochastic environments, but its efficiency can decay exponentially with the size of the ...
This paper proposes an emotion model for life-like agents with emotions and motivations. This model consists of reactive and deliberative mechanisms. The former generates low-leve...
In recent years, there have been several proposals that extend the expressive power of Bayesian networks with that of relational models. These languages open the possibility for t...
This paper discusses the design and implementation of ESSPL, an expert system which generates security plans for alarm systems (Figure 1). Security planning is the task of determi...
One difficulty with existing theoretical work on HTN planning is that it does not address some of the planning constructs that are commonly used in HTN planners for practical appl...
Temporal plans permit significant flexibility in specifying the occurrence time of events. Plan execution can make good use of that flexibility. However, the advantage of executio...
Ioannis Tsamardinos, Nicola Muscettola, Paul H. Mo...